This research develops a machine-learning and data-assimilation framework that combines idealized and operational Earth systems models into a high-resolution, physically realistic “bridging model.” Applied to the El Niño–Southern Oscillation, the approach improves climate simulation accuracy while enabling exploration of alternative climate regimes and physically consistent what-if scenarios.

This research examines how different sea turtle species uniquely shape marine ecosystems through their feeding behaviors. Studying green, loggerhead, and Kemp’s ridley turtles along Florida’s Gulf Coast, the work reveals species-specific ecological functions involving seagrass grazing, sediment mixing, and food web interactions that contribute to ecosystem resilience and coastal conservation.